Skip to main content
SpringerLink
Log in

Protocol for Dynamic Load Distributed Low Latency Web-Based Augmented Reality and Virtual Reality

  • Conference paper
  • First Online:
Computational Intelligence in Communications and Business Analytics (CICBA 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1956))

  • 70 Accesses

Abstract

The content entertainment industry is increasingly shifting towards Augmented Reality/Virtual Reality applications, leading to an exponential increase in computational demands on mobile devices. To address this challenge, this paper proposes a software solution that offloads the workload from mobile devices to powerful rendering servers in the cloud. However, this introduces the problem of latency, which can adversely affect the user experience. To tackle this issue, we introduce a new protocol that leverages AI-based algorithms to dynamically allocate the workload between the client and server based on network conditions and device performance. We compare our protocol with existing measures and demonstrate its effectiveness in achieving high-performance, low-latency Augmented Reality/Virtual Reality experiences.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bray, T.: The JavaScript Object Notation (JSON) Data Interchange Format. RFC 7159(2014), 1–16 (2014)

    Google Scholar 

  2. Carrascosa, M., Bellalta, B.: Cloud-gaming: analysis of google stadia traffic. arXiv:2009.09786 (2020)

  3. Chatzopoulos, D., Bermejo, C., Huang, Z., Hui, P.: Mobile augmented reality survey: from where we are to where we go. IEEE Access 5(2017), 6917–6950 (2017). https://doi.org/10.1109/ACCESS.2017.2698164

    Article  Google Scholar 

  4. Chen, D.-Y., El-Zarki, M.: Impact of information buffering on a flexible cloud gaming system. In: Proceedings of the 15th Annual Workshop on Network and Systems Support for Games (Taipei, Taiwan) (NetGames 2017), pp. 19–24. IEEE Press (2017)

    Google Scholar 

  5. (2006) Chen, J.-W., Kao, C.-Y., Lin, Y.-L.: Introduction to H.264 advanced video coding. In: Proceedings of the 2006 Asia and South Pacific Design Automation Conference vol. 2006, pp. 736–741 (2006). https://doi.org/10.1109/ASPDAC.2006.1594774

  6. Fette, I., Melnikov, A.: The WebSocket Protocol. RFC 6455(2011), 1–71 (2011)

    Google Scholar 

  7. Furht, B. (ed.) JPEG, pp. 377–379. Springer, Boston (2008). https://doi.org/10.1007/978-0-387-78414-4_98

  8. Furht, B., (ed.) Portable Network Graphics (PNG), pp. 729–729. Springer, Boston (2008). https://doi.org/10.1007/978-0-387-78414-4_181

  9. IEEE Digital Reality 2020 (accessed September 16, 2020). Standards. IEEE Digital Reality. https://digitalreality.ieee.org/standards 13 AIVR 2021, July 23-25, 2021, Kumamoto, Japan Sahil Athrij, Akul Santhosh, Rajath Jayashankar, Arun Padmanabhan, and Jyothis P

  10. Kiyokawa, K., Billinghurst, M., Campbell, B., Woods, E.: An occlusion capable optical see-through head mount display for supporting co-located collaboration. In: The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, 2003. Proceedings, pp. 133–141 (2003). https://doi.org/10.1109/ISMAR.2003.1240696

  11. Kooper, R., MacIntyre, B.: Browsing the real-world wide web: maintaining awareness of virtual information in an AR information space. International Journal of Human-Computer Interaction 16(3), 425–446 (2003). https://doi.org/10.1207/S15327590IJHC1603_3

    Article  Google Scholar 

  12. Langlotz, T., Nguyen, T., Schmalstieg, D., Grasset, R.: Next generation augmented reality browsers: rich, seamless, and adaptive. Proc. IEEE 102(2), 155–169 (2014)

    Article  Google Scholar 

  13. Lee, K., et al.: Outatime: using speculation to enable low-latency continuous interaction for mobile cloud gaming. In: Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services (Florence, Italy) (MobiSys 2015). Association for Computing Machinery, New York, NY, USA, pp. 151–165 (2015). https://doi.org/10.1145/2742647.2742656

  14. Liu, L., et al.: Deep learning for generic object detection: a survey. arXiv:1809.02165 (2019)

  15. Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21–37. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46448-0_2

    Chapter  Google Scholar 

  16. Huynh, L.N., Lee, Y., Balan, R.K.: DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications. In: MobiSys, Tanzeem Choudhury, Steven Y. Ko, Andrew Campbell, and Deepak Ganesan (Eds.). ACM, pp. 82–95 (2017). http://dblp.unitrier.de/db/conf/mobisys/mobisys2017.html

  17. MacIntyre, B., Hill, A., Rouzati, H., Gandy, M., Davidson, B.: The Argon AR Web browser and standards-based AR application environment. In: 2011 10th IEEE International Symposium on Mixed and Augmented Reality, pp. 65–74 (2011). https://doi.org/10.1109/ISMAR.2011.6092371

  18. Olsson, T., Salo, M.: Online user survey on current mobile augmented reality applications. In: 10th IEEE International Symposium on Mixed and Augmented Reality. ISMAR 2011, pp. 75–84 (2011). https://doi.org/10.1109/ISMAR.2011.6092372

  19. Oufqir, Z., El Abderrahmani, A., Satori, K.: ARKit and ARCore in serve to augmented reality. In: 2020 International Conference on Intelligent Systems and Computer Vision (ISCV), pp. 1–7 (2020). https://doi.org/10.1109/ISCV49265.2020.9204243

  20. PTCGroup: Vuforia developer portal (2020). https://developer.vuforia.com/

  21. Qiao, X., Ren, P., Dustdar, S., Liu, L., Ma, H., Chen, J.: Web AR: a promising future for mobile augmented reality-state of the art, challenges, and insights. Proc. IEEE 107(4), 651–666 (2019). https://doi.org/10.1109/JPROC.2019.2895105

    Article  Google Scholar 

  22. Redmon, J. Farhadi, A.: YOLO9000: better, faster, stronger. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6517–6525 (2017). https://doi.org/10.1109/CVPR.2017.690

  23. Rouzati, H., Cruiz, L., MacIntyre, B.: Unified WebGL/CSS scene-graph and application to AR. In: Proceedings of the 18th International Conference on 3D Web Technology (San Sebastian, Spain) (Web3D 2013). Association for Computing Machinery, New York, NY, USA, p. 210 (2013). https://doi.org/10.1145/2466533.2466568

  24. Shea, R., Sun, A., Fu, S., Liu, J.: Towards fully offloaded cloud-based AR: design, implementation and experience. In: Proceedings of the 8th ACM on Multimedia Systems Conference (Taipei, Taiwan) (MMSys 2017). Association for Computing Machinery, New York, NY, USA, pp. 321–330 (2017). https://doi.org/10.1145/3083187.3084012

  25. Sun, N., Zhu, Y., Hu, X.: Faster R-CNN based table detection combining corner locating. In: 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE Computer Society, Los Alamitos, CA, USA, pp. 1314–1319 (2019). https://doi.org/10.1109/ICDAR.2019.00212

  26. Duong, T.N.B., Zhou, S.: A dynamic load sharing algorithm for massively multiplayer online games. In: The 11th IEEE International Conference on Networks, 2003. ICON2003, pp. 131–136 (2003). https://doi.org/10.1109/ICON.2003.1266179

  27. Tao, Y., Zhang, Y., Ji, Y.: Efficient computation offloading strategies for mobile cloud computing. In 2015 IEEE 29th International Conference on Advanced Information Networking and Applications, pp. 626–633 (2015). https://doi.org/10.1109/AINA.2015.246

  28. Zhou, X., Gong, W., Fu, W., Du, F.: Application of deep learning in object detection. In: 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS), pp. 631–634 (2017). https://doi.org/10.1109/ICIS.2017.7960069

  29. Zimmermann, C., Brox, T.: Learning to estimate 3D hand pose from single RGB images. In: IEEE International Conference on Computer Vision (ICCV) (2017). https://lmb.informatik.uni-freiburg.de/projects/hand3d/https://arxiv.org/abs/1705.01389

Download references

Author information

Authors and Affiliations

  1. Cochin University of Science and Technology, Kalamassery, Kochi, Kerala, India

    T P Rohit & Sasi Gopalan

  2. University of Washington, Seattle, WA, 98195, USA

    Sahil Athrij

Authors
  1. T P Rohit
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sahil Athrij
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sasi Gopalan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T P Rohit .

Editor information

Editors and Affiliations

  1. Kalyani Government Engineering College, Kalyani, India

    Kousik Dasgupta

  2. Assam University, Silchar, India

    Somnath Mukhopadhyay

  3. University of Kalyani, Kalyani, West Bengal, India

    Jyotsna K. Mandal

  4. Visvabharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Rohit, T.P., Athrij, S., Gopalan, S. (2024). Protocol for Dynamic Load Distributed Low Latency Web-Based Augmented Reality and Virtual Reality. In: Dasgupta, K., Mukhopadhyay, S., Mandal, J.K., Dutta, P. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2023. Communications in Computer and Information Science, vol 1956. Springer, Cham. https://doi.org/10.1007/978-3-031-48879-5_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48879-5_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48878-8

  • Online ISBN: 978-3-031-48879-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation